This Title All WIREs
How to cite this WIREs title:
WIREs Data Mining Knowl Discov
Impact Factor: 4.476

Automatic question generation

Full article on Wiley Online Library:   HTML PDF

Can't access this content? Tell your librarian.

Abstract Automatic generation of semantically well‐formed questions from a given text can contribute to various domains, including education, dialogues/interactive question answering systems, search engines, and more. It is well‐known as a challenging task, which involves the common obstacles of other natural language processing (NLP) activities. We start this advanced review with a brief overview of the most common automatic question generation (AQG) applications. Then we describe the main steps of a typical AQG pipeline, namely question construction, ranking, and evaluation. Finally, we discuss the open challenges of the AQG field that still need to be addressed by NLP researchers. This article is categorized under: Algorithmic Development > Text Mining

Browse by Topic

Algorithmic Development > Text Mining

Access to this WIREs title is by subscription only.

Recommend to Your
Librarian Now!

The latest WIREs articles in your inbox

Sign Up for Article Alerts